Great Lakes Ensemble
In 2015, the Great Lakes Integrated Sciences and Assessments program (GLISA) formally started the development of a Great Lakes Ensemble of future climate projections and guidance for practitioners in the Great Lakes region. This project is motivated by the need for high-quality, regionally relevant climate projections for use in climate change adaptation work. The current challenge is not a lack of climate projections to choose from, rather, today’s practitioner is faced with an overwhelming large quantity of projections with very little guidance on how to choose the most relevant ones for their work.
The Ensemble project aims to address challenges associated with choosing and using climate projections by summarizing projections for adaptation audiences and providing expert guidance for advanced users. Ultimately, the Ensemble project as a whole is intended to increase the capacity of practitioners to be informed consumers of climate information.
Our Great Lakes Ensemble project started in 2015 to inventory and evaluate future climate simulations to determine which models offer the highest quality information for the Great Lakes region. This has evolved into a community of experts and practitioners in our Scientific Advisory Committee and Practitioner Working Group, with whom we have co-developed a climate model evaluation framework. In Phase II we have: a) applied the framework to evaluate the presence of the lakes in CMIP5 simulations (Briley et al. 2021), b) assessed model biases of temperature and precipitation for two CMIP5 ensembles (the North American Coordinated Regional Downscaling Experiment and NA-CORDEX, and the University of Wisconsin’s Regional Climate Model version 4, and c) investigated the representation of lake-effect precipitation using a clustering technique. As a result, we developed our suite of ‘climate model consumer reports’ (Briley et al. 2020), a novel approach to communicate this information to practitioners, which includes a buyer’s guide and climate model report cards for each evaluated ensemble. Also, with input from the SAC and PWG, we developed several guidance resources to address users’ needs in the region, including for bias and bias correction (Gates and Rood 2021), and climate forcing scenarios (Briley et al. 2021).
Briley, L. J., Ashley, W. S., Rood, R. B., & Krmenec, A. (2015). The role of meteorological processes in the description of uncertainty for climate change decision-making. Theoretical and Applied Climatology, 127, 643–654. http://dx.doi.org/10.1007/s00704-015-1652-2
Briley, L. J., Rood, R. B., & Notaro, M. (2021). Large lakes in climate models: A Great Lakes case study on the usability of CMIP5. Journal of Great Lakes Research, 47(2), 405–418. https://doi.org/10.1016/j.jglr.2021.01.010
Briley, L., Dougherty, R., Blackmer, E. D., Troncoso, A. V., Rood, R. B., Andresen, J., & Lemos, M. C. (2020). Increasing the usability of climate models through the use of consumer-report style resources for decision making. Bulletin of the American Meteorological Society, 101(10), E1709–E1717. https://doi.org/10.1175/BAMS-D-19-0099.1
Briley, L., Dougherty, R., Wells, K., Hercula, T., Notaro, M., Rood, R., Andresen, J., Marsik, F., Prosperi, A., Jorns, J., Channell, K., Hutchinson, S., Kemp, C., & Gates, O. (2021). A practitioner’s guide to climate model scenarios. Great Lakes Integrated Sciences and Assessments (GLISA). https://glisa.umich.edu/practitioner-guides/
Gates, O. & Rood, R. (2021). In global climate models, we trust? An introduction to trusting global climate models and bias correction. Great Lakes Integrated Sciences and Assessments (GLISA). http://glisa.umich.edu/an-introduction-to-trusting-global-climate-models-and-bias-correction
Great Lakes Integrated Sciences and Assessments (GLISA). (2017). Great lakes ensemble: March 2016-March 2017 progress report. http://glisa.umich.edu/media/files/Ensemble_Progress_Report_March_2017.pdf
Notaro, M., Jorns, J., & Briley, L. (2022). Representation of lake-atmosphere interactions and lake-effect snowfall in the Laurentian Great Lakes Basin among HighResMIP global climate models. Journal of the Atmospheric Sciences, 79(5), 1325-1347. https://doi.org/10.1175/JAS-D-21-0249.1
Scientific & Stakeholder Advisory Groups
The Ensemble project is informed by external two groups, a scientific advisory committee and stakeholder working group, that are made up of a diverse set of scientists and adaptation professionals who bring valuable regional perspectives to this work. Each of these groups is bi-national, including both U.S. and Canadian partners, which is essential since the Ensemble’s geographic scope includes any state that touches a Great Lake and southern Ontario.
The Ensemble’s Scientific Advisory Committee (SAC) is helping GLISA:
- Better understand the interactions between the lakes and our regional climate
- Develop a set of model evaluation standards specific to the Great Lakes region
- Reach out to end users who can help inform products of the ensemble
The Ensemble’s Stakeholder Working Group (WG) is:
- Providing feedback on existing GLISA products that are commonly used by stakeholders (i.e., city climatologies, Great Lakes Adaptation Data Suite (GLADS))
- Co-developing new stakeholder products with GLISA (i.e., scenarios, consumer-style data guides, and more)
- Investigating with GLISA how to scale products to larger audiences and increase usability across the region
Scientific Advisory Committee (SAC) members and Stakeholder Working Group (SWG) members:
- Joseph Barsugli (SAC) University of Colorado/NOAA Earth System Research Laboratory
- Tim Boring (WG) Michigan Agricultural Advancement
- Devon Brock-Montgomery (WG) Unaffiliated, formerly with the Bad River Band
- Daniel Brown (WG) Huron River Watershed Council
- Eric Clark (WG) Sault Ste. Marie Tribe of Chippewa Indians
- Frances Delaney (SAC) Environment and Climate Change Canada
- Ankur Desai (WG) University of Wisconsin-Madison
- Andre Erler (SAC) Aquanty
- Rebecca Esselman (WG) Huron River Watershed Council
- Edmundo Fausto (WG) City of St John’s
- Elizabeth Gibbons (WG) American Society of Adaptation Professionals
- Drew Gronewold (SAC) University of Michigan
- Christopher Hoving (WG) Michigan Department of Natural Resources/Michigan Climate Coalition
- Greg Mann (WG) National Weather Service-Detroit
- Glenn Milner (SAC) Climate Risk Institute
- Biljana Music (SAC) Ouranos, Consortium on Regional Climatology and Adaptation to Climate Change
- Michele Richards (WG) Michigan Army National Guard/Michigan Climate Coalition
- Peter Snyder (SAC) University of Minnesota
Sustained Assessment of Climate Models
Many climate models do not provide credible information for the Great Lakes region, because they poorly represent the Great Lakes and lake-land-atmosphere dynamics. GLISA performs ongoing evaluation of global and regional climate models to determine which ones best represent the climate of the Great Lakes region so we can deliver the highest quality information to our stakeholders. Our assessment of models is part of our larger Great Lakes Ensemble project, and includes evaluation of the representation of lakes and important lake-land-atmosphere processes and climate model biases. We also assess data processing techniques (i.e., downscaling and bias correction) and develop guidance for practitioners to use when choosing and/or using climate projections in their work.
To date, GLISA has evaluated models from the following ensembles:
- 40 GCMs from the Fifth Climate Model Intercomparison Project (CMIP5)
- 19 dynamically downscaled simulations from the North-American Coordinated Regional Climate Downscaling Experiment (NA-CORDEX)
- 6 dynamically downscaled simulations from the UW-RegCM4 dataset
Visit the sustained assessment of climate models project page.
Climate Information Consumer Reports
Consumers of climate model information can find it difficult to assess which models and projections are best for their particular needs. One challenge consumers face is the abundance of models and projections. On the other hand, consumers may lack information on a given model’s quality, trade-offs, and suitability for a particular geographic region or type of decision. Traditionally, consumer reports have provided potential consumers with an array of information on available products and services to help them make informed decisions. To guide climate information consumers, the GLISA team developed a suite of “climate model consumer-reports.” To develop the reports, GLISA reviewed examples of consumer reports from other sectors, relied on the feedback and advice of real-world consumers, and incorporated expert guidance from model developers. The content and formatting of our climate model consumer reports respond to and evolve with needs of consumers and incorporate our research in usability of climate knowledge. We pose that climate model consumer reports, especially when developed in the context of trusted relationships between users and creators of climate knowledge, contribute to making climate information more relevant to and usable by practitioners.
- Climate Model Report Cards
- Climate Model Buyer’s Guides
- Cross Model Comparison Charts
- Journal article (published in BAMS June 2020)
GLISA developed a proof of concept for packaging climate information into consumer-report-style resources, which have been taken up by practitioner audiences. This early success demonstrates the usability of our approach and will guide how GLISA packages climate information in the future.
GLISA led the development of several new consumer-report style resources for practitioners in the region.
GLISA develops guidance with and for practitioners in the region to increase the usability of climate information needed in adaptation planning. Each guidance resource is designed to bridge a specific climate information gap that practitioners often face. Much of our guidance is targeted toward climate data use to aid practitioners who are selecting and using climate projections in their work. Other areas of guidance are developed as GLISA identifies need for it within the region.
Visit the Practitioner Guides page to learn more about the resources that are available.
A Scenarios Guide for Climate Change Adaptation
In response to the growing demand for expert-led guidance on scenario planning, GLISA is developing a practitioner’s guide to the scenario planning process. This guide is being co-developed with GLISA’s Ensemble Scientific Advisory Committee (SAC) and Stakeholder Working Group (SWG) to ensure scientific accuracy and practitioner relevancy. It will be a resource for better understanding what scenarios are and how to develop them, and includes a tutorial and accompanying workbook for walking through the scenario planning process using GLISA’s approach. Although much of the guide reflects GLISA’s experience working in the Great Lakes, it is intended to serve a national audience and we anticipate publishing it on the U.S. Climate Resilience Toolkit and climate.gov.
- A synthesis guide summarizing different types of climate scenarios used in scenario planning (anticipated)
- A Practitioner’s Guide to Climate Forcing Scenarios (i.e., RCPs) (anticipated)
Frequently Asked Questions
What is an ensemble?
“Ensembles” are collections of data from multiple climate model simulations. Typically, an ensemble consists of data from several different climate models to show the range of variability. Given that no single model perfectly simulates the dynamics governing any scale of climate (global, regional, or local), the reliance on several model simulations allows users to better characterize the range of possible future climate outcomes. To that end, ensembles provide measures of uncertainty related to the model-based information.
Why is GLISA developing a Great Lakes Ensemble?
Many climate models do not provide credible information for the Great Lakes region, because they poorly represent the Great Lakes and lake-land-atmosphere dynamics. GLISA is evaluating several climate model data sets to establish a set (ensemble) that best represent important components of Great Lakes regional climate. In addition to model evaluation, data processessing (i.e., downscaling) methods will also be assessed for their impact on the quality of the data.
How is GLISA developing the Great Lakes Ensemble?
There is no single standard methodology for developing ensembles, but using simple model selection procedures with detailed documentation is one way to build a credible ensemble.1 GLISA is developing a regional model evaluation framework to assess an initial set of widely accepted climate model data sets (global and regional). The most basic evaluation criteria include:
1. The model provides data that is continuous in space and time
2. Important climate processes are represented
a. The Great Lakes are simulated in the model
b. A signal of the lakes (i.e., effect of the lakes on regional air temperatures and precipitation) is apparent
3. Any downscaling method applied to the model does not assume climate stationarity
- Overland, J. E., Wang M., Bond N. A., Walsh J. E., Kattsov V. M., & Chapman W. L. (2011). Considerations in the Selection of Global Climate Models for Regional Climate Projections: The Arctic as a Case Study*. Journal of Climate. 24(6), 1583 – 1597. http://dx.doi.org/10.1175/2010JCLI3462.1
- McSweeney, C. F., Jones R. G., & Booth B. B. B. (2012). Selecting Ensemble Members to Provide Regional Climate Change Information. Journal of Climate. 25(20), 7100 – 7121. http://dx.doi.org/10.1175/JCLI-D-11-00526.1
- Stainforth, D. A., Downing T. E., Washington R., Lopez A., & New M. (2007). Issues in the interpretation of climate model ensembles to inform decisions. Philosophical Transactions Of The Royal Society A-Mathematical Physical And Engineering Sciences. 365, 2163-2177. 10.1098/rsta.2007.2073
“I’m writing to offer my congratulations on developing and producing GLISA’s ‘A Practitioner’s Guide to Climate Model Scenarios.’ That overview is easily the best I’ve seen in laying out the model basics and process questions that users need to consider as they work to incorporate model projections into impacts and decision processes.”
Deputy Director, Southeast Climate Adaptation Science Center
- University of Colorado Boulder
- Huron River Watershed Council
- Sault Ste. Marie Tribe of Chippewa Indians
- Environment and Climate Change Canada
- University of Wisconsin-Madison
- University of Michigan
- Michigan Department of Natural Resources
- Michigan Climate Coalition
- Michigan Army National Guard
- University of Minnesota
- Amec Foster Wheeler
- Michigan Agriculture Advancement
- Climate Risk Institute
- A Practitioner’s Guide to Climate Model Scenarios
- Climate Model Buyer’s Guide
- Great Lakes Ensemble: A Quick Introduction
- Increasing the Usability of Climate Models through the Use of Consumer-Report-Style Resources for Decision-Making
- The role of meteorological processes in the description of uncertainty for climate change decision-making
- Large lakes in climate models: A Great Lakes case study on the usability of CMIP5
- Great Lakes Ensemble Model Evaluation Framework
- Great Lakes Ensemble 2018 Progress Report
- Great Lakes Ensemble 2017 Progress Report
- Representation of Lake–Atmosphere Interactions and Lake-Effect Snowfall in the Laurentian Great Lakes Basin among HighResMIP Global Climate Models